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[Please go to \'Settings\' to change your Tagline]Fri, 31 Jul 2015 10:35:00 +0000en-UShourly1http://wordpress.org/?v=3.9.2The Venture Funding Boom In Biotech: A Few Things It’s Nothttp://www.forbes.com/sites/brucebooth/2015/07/23/the-venture-funding-boom-in-biotech-a-few-things-its-not/
http://www.forbes.com/sites/brucebooth/2015/07/23/the-venture-funding-boom-in-biotech-a-few-things-its-not/#commentsThu, 23 Jul 2015 10:56:00 +0000http://blogs.forbes.com/brucebooth/?p=1119Venture-backed biotechs continue their blistering pace of funding. According to the latest MoneyTree Report from PricewaterhouseCoopers (PwC) and the National Venture Capital Association (NVCA), with data from Thomson Reuters, over $2.1B was invested in biotech companies in 2Q 2015, bringing the year to date total to almost $4B(covered here, here). Four of the last five quarters are amongst the largest record-setting quarters in ten years.

It’s one of the best periods for biotech funding in the history of the industry, offering an opportunity for emerging companies to scale and develop their pipelines more significantly than ever before.

But the averages and top-line data convey only so much – huge fund flows, big year-on-year gains, and meaningless average. There’s much more than meets the eye, and I thought it worth reviewing a more nuanced and data-rich look at what this hot funding climate is not as a way to frame up a few broader observations. Here are four things the current market is not:

1. It’s not “venture” in the traditional sense. The big recent uptick above the normal $1-1.5B that’s invested quarterly into biotech isn’t coming from the coffers of venture capitalists, it’s coming from hedge funds and public market “crossover” investors. Take as an example the top 10 biotech deals of the second quarter – Denali, Adaptive, RegenX, CytomiX, Melinta, Unum, Dimension, Voyager, Jounce, and Edge. My rough deal-by-deal calculation, based on participating investor mix, is that 67% of the $920M raised by this group came from non-venture sources. These include biotech crossover fund specialists like Deerfield, Brookside, RA Capital, and Wellington, but also significant contributions from alternative investment groups like the Alaska Permanent Fund and Malin Plc. Although lots of new venture funds are being raised, they get deployed over 5-7 years, not a few quarters – so while it is fair to say venture is booming, the real driver of the financing spike in the quarterly data has been from the eager participation of non-traditional biotech investors.

2. It’s not distributed broadly. The concentration of these “venture” dollars in the biggest deals is significant. The top 10 deals (like the list above), which in any given period represent roughly the largest 7-8% of the financings, accrued 45% of all the biotech funding. The top deals have captured a similar proportion for the past twenty quarters, as per the chart below. This concentration of funding reflects a very high Gini Coefficient, to steal a term from income inequality literature; there are relatively few “haves” and lots of “have-nots” when it comes to the flow of funding. More broadly across the distribution of deals, this funding bias creates an enormous skew in the “funding per company” metrics over time, making the “average” an utterly meaningless snapshot (since its not a normal distribution at all). The bottom quartile and median metrics are almost identical, with the top quartile significantly higher (see second graph below). It’s also worth noting that the big financings we commonly hear about (like the top 10 ones!) are in the rarefied few, above the top decile of financings; in fact, the top quartile metric for funding per company has only been above a “paltry” $20M in three quarterly periods across the past ten years. And the median biotech financing, regardless of stage, is still not that much higher than $4-8M – way below the average figures.

3. It’s not increasing the number of biotechs that get financed. Unlike software venture capital, which is backing 2x more companies today than five years ago, the biotech venture community isn’t funding an expanding ecosystem of private companies. It’s been a relatively constant funding pace for the past decade of around 100-150 per quarter. So the uptick in funding of late is just leading to more money for the same number of companies; and, in light of #2 above, its really just more money for the top few companies. Hopefully it’s being deployed wisely in a manner that can efficiently convert invested capital into value creation (the essence of “capital efficiency”).

4. It’s also not leading to increased startup formation. The number of biotech startups receiving their first financings continues to be flat despite the unprecedented later stage demand, reflecting the massively constrained startup ecosystem discussed previously (here, here, here). While the numbers of startups are flat (25-30 per quarter), there’s an even bigger spike in funding amount per first financing in recent quarters. The median funding per first financing in a biotech startup company hit $10M this quarter, which is 300-400% higher than the last decade’s running average. In fact, the top quartile of these first financings are now very similar to the top quartile of all stages of financings – around $20M – which is a real surprise. It’s fair to say that significantly more capital is backing a constant number of new startups – reflecting the “launching” of larger, more highly powered-up startups by a handful of venture groups.

So what does this all mean, besides being a good reminder that averages and top-level data always leave a lot of nuanced insight behind? Here are three questions worth reflecting on:

What will happen when the public and non-traditional investors decide they don’t want to allocate their capital to private biotech companies? They have significantly inflated the pool of capital available today, but they could quickly depart if they start losing money in the space or if the overall market sentiment turns against the biotech sector (big clinical failures?), healthcare (pricing issues?), or equities as a whole. Its unclear how long-term and sustainable many of these non-venture players are in the biotech funding environment. It would be great to have them around for the long term, helping us launch and build great companies. But I think its likely more a matter of when, not if, this cadre of investors cools towards biotech (at least temporarily), and so young companies should be executing strategies today that account for these future funding contingencies (e.g., identifying and cultivating potential partners, creating flexible operating models with variable burn rates, etc…).

Are we over-funding and losing discipline? Anytime buoyant markets channel more capital than the historic norms into a space, questions around bubbles and over-funding get raised. It’s a frequent refrain in biotech today – is their a funding and valuation bubble? As a long-term investor and company-builder, the critical question to focus on is whether the current wave of funding is leading to governance complacency and a lack of discipline in how companies use the proceeds of these financings. Is the capital efficiently being deployed? Common mistakes one would expect in an overly permissive environment would be building excessive amounts of non-critical fixed infrastructure, hiring big teams too rapidly, locking into long-term expensive leases for too much space, funding immature science projects before they prove themselves, etc… I’m sure there are examples of these happening right now, but its not endemic: I still sense that most biotech teams and their boards are being thoughtfully disciplined around most of these areas of growth and spending.

Is there sufficient venture creation of new startups to refresh the ecosystem? Asked another way, what’s the right number of private biotech companies at steady state in a healthy ecosystem? I’m not sure, but it’s clear we aren’t creating an expanding pool of venture-backed biotechs, and the IPO and M&A exit markets are removing them from the venture ecosystem at a rapid clip. The number of compelling private biotechs today is far less than it was just two years ago, and many BD teams in Pharma know this as they struggle to identify compelling early stage partners – especially in areas like cardiovascular disease and neuroscience. We simply aren’t creating enough new corporate substrate as a sector. As a supplier of new companies, Atlas and other early stage firms are in a good position to feed future demand for innovation, which bodes well for venture returns – but a healthier ecosystem would be one that expands the number of participants, albeit at a modest and measured pace.

With this funding backdrop, it’s an exciting time to be a young biotech company – especially if you can broaden your sources of long-term investment capital, scale your company with less dilutive financing rounds, and deploy the funds with discipline and diligence. Only time will tell how all these variables play out, but every company (and its investors) will get judged by hindsight soon enough.

]]>http://www.forbes.com/sites/brucebooth/2015/07/23/the-venture-funding-boom-in-biotech-a-few-things-its-not/feed/1Volatile Mixture: Young Biotechs’ Stock Market Rollercoasterhttp://www.forbes.com/sites/brucebooth/2015/07/10/volatile-mixture-young-biotechs-stock-market-rollercoaster/
http://www.forbes.com/sites/brucebooth/2015/07/10/volatile-mixture-young-biotechs-stock-market-rollercoaster/#commentsFri, 10 Jul 2015 12:14:00 +0000http://blogs.forbes.com/brucebooth/?p=1112The stock market has been a wild ride of late – big moves up and down, NYSE getting halted, Grexit, China – lots of reasons for added skittishness. The VIX index, which measures the volatility of the S&P500, has gone up more than 50% in the last twelve trading days, into the range seen only a handful of times since mid-2012.

But the VIX measures the bigger end of the stock market. Biotech is a high beta equity sector, meaning it has a tendency to swing more than other stocks in respond to market changes. Within the biotech sector, younger small cap stories are notoriously more volatile, but historically there’s been little aggregate data given how few biotech companies made it public. But that’s changed in the past two years, so it may be more useful to examine the ups and downs of these newly minted IPO stocks.

First, the dataset used here tracks 112 biotech’s that went public in the 24 months of 2013-2014, and are still trading today; for these stocks, the daily closing prices were compiled and day-to-day changes were analyzed. Here’s the summary of the findings.

As a group, this cohort of young companies has rollercoaster volatility, as you might expect. On a typical day since start of trading this year (122 days through June 26), 43% of stocks in this group move down by more than 1% and 46% move up over 1% (meaning only 11% trade between 1% and -1%). Beyond that, the outliers are significant: 8% of the stocks in this group move down more than 5% on an average trading day, and 11% move up more than 5%.

Below is a chart that captures the cumulative distribution of daily stock changes. With 112 stocks coming into the markets over this period, this distribution represents over 37,000 daily closing prices.

Digging into the individual stocks themselves, an annualized historic statistical volatility can be calculated (as described here). Here’s a table with the ten most and least volatile stock tickers, with a comparison to some large-cap biotechs and the NASDAQ Biotech Index (IBB). It also tracks some of the more high profile IPOs of the past couple years.

As expected, the volatilities of even the least volatile group of stocks are much higher than their large cap comparators, which range from 25-37% across names like Amgen, Gilead, Biogen, Regeneron, and Celgene.

High flying “premium” valuation stocks have also seen significant day-to-day volatility, with annualized rates in the high double digits: for example, Juno Therapeutics has shown annualized statistical volatility of 90% given the dynamic stock moves around news in the CAR-T field. Of the 129 trading days for Juno in this dataset, 16% were moves upward by over 5%, and 12% were moves downward greater than 5%. Another example is bluebird bio, which has an annualized volatility above 80%, reflecting the excitement in its programs and the gene therapy space; 15% of its~500 trading days have delivered stock movements greater than +/- 5%. Further, the most volatile stocks in this IPO cohort reflect crazy levels of stock volatility: Neuroderm, Nephrogenix, and Vascular Biogenics all have annualized statistical volatilities north of 150%.

It’s well understood by most investors that these stocks should be more volatile. They are by and large a thinly traded group, with small floats of outstanding stock and significant insider ownership. The prices of these stocks are therefore easily moved by modest changes in trading volume: in short, small orders can gyrate their pricing. Add this technical trading dynamic to the dynamic newsflow in these areas (e.g., CAR-Ts, gene therapy, orphan cancer drugs) and their specific R&D updates, and it’s a volatile mix.

It would be interesting to compare these “IPO cohort” volatilities with the stocks from past IPO windows (but I haven’t the data nor the time); its not likely that any of the technical fundamentals (like insider ownership, float, etc…) have changed significantly from past vintages, but the level of institutional specialist investing and long/short hedge fund activity in the space has almost certainly increased.

In light of the significant volatility, there are a few takeaways for those of us interested in long-term fundamental investing:

Get a seatbelt and focus on the destination. Buckle into the stock as long as the investment thesis remains intact and the valuation has room to grow into that thesis. Expect lots of ups and downs between now and then. Reconsider as the thesis plays out.

Don’t try to time the market; pick great stories, high impact medicines, and stick with them. Great companies are built over years and decades, not days and months.

If you are an active trader, have fun with the volatility and have your Xanax ready. I have no stomach for that, and hence am in the most-illiquid, long-term part of the biotech sector.

Big macro shocks are likely to further exacerbate these biotechs’ volatilities: although gene therapy has little to do with Grexit, traders correlate everything during market meltdowns. Given the macro issues today and on the horizon, expect things to stay exciting.

The capital markets in small-cap biotech are, as usual, awash in volatility. Accessing the public markets is essential for scaling new business and accessing the required capital, but it obviously come with expectation of potentially distracting and volatile stock movements. The key for management teams and their long-term investors is to not let daily or weekly or even monthly moves in your stock consume your attention. Build long-term value and the rest will come.

As many others have said, “the markets are a great servant but a bad (and volatile) master”.

]]>http://www.forbes.com/sites/brucebooth/2015/07/10/volatile-mixture-young-biotechs-stock-market-rollercoaster/feed/2External Innovation: Force Multiplier For R&Dhttp://www.forbes.com/sites/brucebooth/2015/06/26/external-innovation-force-multiplier-for-rd/
http://www.forbes.com/sites/brucebooth/2015/06/26/external-innovation-force-multiplier-for-rd/#commentsFri, 26 Jun 2015 15:16:00 +0000http://blogs.forbes.com/brucebooth/?p=1103External models of R&D innovation are the rage in Pharma today, as they should be – the future of our industry depends on a great deal more rather than less collaboration.

In a very healthy way, lots of experiments are being done across the ecosystem and the final scorecard for what worked and what didn’t is years from being tallied up; however, the early biomarkers are positive and it’s a widely-held belief that a critical element of exceptional R&D organizations in the future will be creative BD engagement. In short, great BD and R&D are becoming synonymous with each other.

For much of the past decade, most of Big BioPharma has focused on extracting value from the conventional workhorses of partnering: licensing, M&A (including use of risk-sharing biobucks), and R&D collaborations. Over 75% of the most exciting late stage assets in Pharma’s pipelines came via these traditional external sourcing routes (here). These are valuable tools, and are certainly very important for pipeline-building, but they only scratch the surface of what external R&D models can deliver for Pharma.

Beyond the obvious and direct value of accessing new assets or platform technologies, the much more compelling strategic imperative of external innovation initiatives is as a force multiplier for the R&D organization.

Taken seriously enough – as both a percentage of an R&D leadership team’s time and budgetary resourcing – these creative external strategies have the potential to be meaningful culture-change agents to invert the periphery and the core of corporate R&D; they also greatly enhance the breadth and quality of an organization’s exposure to new innovation without smothering it inside the internal bureaucracy; lastly, they provide great leverage to the financial model of R&D via access to different capital sources, the benefits of fractional ownership, and operational flexibility and efficiency. All of these benefits, which are detailed below, aid in the tighter integration of internal R&D efforts with BD. But these can really only be achieved by overcoming a range of established value-destroying mental models, also described below, that are pervasive in R&D today.

Before going through those value-enabling elements of external R&D, it’s worth summarizing and exemplifying the range of models being explored today.

External R&D Toolbox

Conventional BD deal-making around licenses and acquisitions make up a good deal of the external activity for most companies, and that’s likely to continue to be the case; here, though, I’ll focus on the other tools of the craft that are in some ways more intriguing and more explicitly focused on early stage innovation. There are at least three broad types of these creative “external R&D” strategies: direct company engagements, fund-related portfolio approaches, and open innovation models.

]]>http://www.forbes.com/sites/brucebooth/2015/06/26/external-innovation-force-multiplier-for-rd/feed/0Disease-Specific Allocations: The Past Decade Of Venture, IPOs, And Deal-Makinghttp://www.forbes.com/sites/brucebooth/2015/06/15/disease-specific-allocations-the-past-decade-of-venture-ipos-and-deal-making/
http://www.forbes.com/sites/brucebooth/2015/06/15/disease-specific-allocations-the-past-decade-of-venture-ipos-and-deal-making/#commentsTue, 16 Jun 2015 00:59:00 +0000http://blogs.forbes.com/brucebooth/?p=1099Figuring out what disease areas are attracting the most venture funding and deal-related capital in startup and emerging biotech has historically been quite challenging as few if any datasets track it comprehensively. But late last week, on the eve of BIO, a significant piece of analysis should shine some light on the topic.

David Thomas and Chad Wessel of BIO take a very data-rich crack at addressing this in their new June 2015 report titled “Emerging Therapeutic Company Investment and Deal Trends”. It covers much of the ground of their prior venture-funding report from February 2015 (here), and extends it with more analytics around deal-making and public market financing (IPOs, Follow-Ons). For those data-junkies interested in the specifics, it’s well worth reading.

While there are many nuggets in the report, I wanted to highlight one interesting angle in the data: the relative allocation of capital across disease areas over the ten-year period of 2005-2014 between the venture-backed private therapeutic biotech space and two downstream markets, namely IPO funding flows and BD deals (licensing and R&D-stage M&A).

For background, over $38 billion was deployed by venture capital into therapeutic biotech companies over the ten-year period in nearly 3000 financings. During that time, there were 173 therapeutic biotech IPOs raising over $13 billion (most of which were in the last two years), and over 1500 BD-transactions reflecting over $110 billion in upfronts and milestones spread across licensing deals and R&D-stage M&A. So it’s a fairly extensive dataset.

Comparing these three markets gives an interesting decadal view of where funding has gone and what areas have attracted the most attention. The three charts below capture the allocation across different areas (top chart), as well as the relative over/under-allocation versus where venture funding has gone (e.g., IPOs vs venture and deal-making vs venture in the bottom two charts).

A few observations:

Oncology is remarkably steady at roughly 25% of the fund flows across all three markets. I’m sure there are some changes within oncology: for example, targeted kinase inhibitors were probably well represented in the earlier years of the dataset (2005-2009) vs more recently the burst of I/O and engineered cell therapy funding.

Hematology (outside of oncology) appears to have been funded much more significantly on a relative basis (12% vs 3%) by IPO investors than the venture community. This includes disease areas like “Blood Stimulators, Coagulation agents, Anemia, Antithrombotic, Chronic Venous Ulcers, Peripheral Arterial Disease (PAD), Sickle Cell Disease, Iron Overload, Hemophilia, and Neutropenia/ Leukopenia”. About 6% of the IPOs over the last decade were in this category. VCs, relative to IPO investors, appear to have under-invested in this area over the decade.

Infectious Diseases stands out as a significant deal-making area, even topping oncology over the past decade. Capital from BD transactions on a relative basis far outstripped the venture and IPO markets in infectious disease (28% vs ~11% of funding). These data suggest that at least when it comes to investing in areas with significant deal interest, venture capital has been under-allocated to infectious diseases over the decade.

Platform companies, as one would expect, were predominantly funded by the venture community vs public investors. By the time these deals get to their IPOs, they’ve established their lead program and the report would classify them as such.

There are obviously many caveats to this analysis, and the methodology section of their report goes through some of these limitations. Fundamentally, the merits of the above data rely on the right classification of companies, which is often quite difficult if the lead program can go in different directions (immunology or oncology, cardiovascular or metabolism, etc…). But in general, it’s an interesting report with a broad range of observations.

Thanks to the analytical team at BIO for sharing these data; have a good #BIO2015!

]]>http://www.forbes.com/sites/brucebooth/2015/06/15/disease-specific-allocations-the-past-decade-of-venture-ipos-and-deal-making/feed/0ASCO 2015: Abstract Thoughts On Cancer And Competitionhttp://www.forbes.com/sites/brucebooth/2015/05/29/asco-2015-abstract-thoughts-on-cancer-and-competition/
http://www.forbes.com/sites/brucebooth/2015/05/29/asco-2015-abstract-thoughts-on-cancer-and-competition/#commentsFri, 29 May 2015 10:35:00 +0000http://blogs.forbes.com/brucebooth/?p=1092With the start of the American Society of Clinical Oncology meeting, all eyes in the biopharma investor community are on Chicago. Social media is alive with #ASCO15 tweets and companies big and small are firing out press releases. Signal from noise will be hard to discern over the next few days.

While it’s hard to know if there will be any positive or negative surprises this year, at least until the weekend is over, a quick “Friday fun” data analysis of the nearly 5,000 abstracts reveals the rather narrow focus of the community’s attention (though I’m likely contributing more to noise than signal).

As one might expect, the word “patient” and “cancer” show up in 90+% of the abstracts at ASCO. Nearly two-thirds of them mention a “treatment” or contain a “clinical” reference. “Chemotherapy” and related regimens appear in about a third, and “antibodies” close to 10%. I share those because they help calibrate my quick survey of the abstracts’ keywords, which, although unscientific, appears to have some merit and align with what you might expect.

The summary of my data-lite analysis is captured below – a chart showing the number of abstracts that mention a particular therapeutic target (out of a couple dozen targets that I assessed, a group of which are presented here):

Two quick takes:

The ErbB family – HER2, EGFR, HER3 – continue to capture tons of attention in the oncology world: despite their discovery over 30 years ago, these tyrosine kinase receptors were three of the top four targets mentioned in abstracts this year. With dozens of cancer drugs attacking these targets, and lots of interest in their gene expression patterns across tumor types, it’s not surprising to see these widely presented in abstracts – though their collective abundance at the top of the league tables was eye-opening, at least to me. Beyond a stable of approved agents, programs are being developed for pan-ErbB activity (Puma, others), mutant-selective inhibition (Clovis, AZ), and many other ErbB-related product profiles. Somewhat amazing that after several decades there’s still a lot more to learn, and apparently a lot more drugs to develop against these various ErbB profiles.

Immuno-oncology checkpoint targets, as expected, light up the list of frequent-fliers in the abstracts: PD-1 and PD-L1 have hundreds of abstracts between them, not surprisingly standing out ahead of other immune targets. Most major oncology players have abstracts involving PD-1, including Merck, Bristol-Myers Squibb, AstraZeneca, Novartis, Roche, and pretty much everyone else. Other T-cell related targets like CTLA-4, TIM-3, OX-40, and LAG-3 round out the list of frequent mentions. Engineered immune cell therapies (CAR-Ts) are found in a couple dozen abstracts, but not nearly as abundant as I expected given the market’s level of interest in those stories. The log-order difference of these “newer” approaches vs PD-1 and the ErbB family mentions is also likely a function of ASCO being a later stage and more solid-tumor oriented meeting than AACR or ASH.

To pressure test the distribution in my brief survey, I also ran through a similar search for abstracts from AACR 2015 from last month; a broadly similar concentration of target-related activity exists, highlighting the intense spotlight on PD-1 and ErbB approaches.

Stepping back from this fun data-lite analysis,the other general conclusion one can draw from the abstracts is that the “March of the Lemmings” (see the link for my 2012 ASCO blog on the topic) is still very much in effect. The industry is largely chasing all the same cancer targets; once validated with clinical data, competition on these emerging high impact targets becomes fierce – as is the case with many of the ErbB and immuno-oncology checkpoint targets today, as well as CD-19 in the CAR-T space. Each of these targets has dozens of preclinical development and clinical stage programs lined up against it.

Although many of these targets have little “clinical risk” left in them (though Amgen’s brodalumab teaches us that even mAbs against similar ligand-receptor pairs can have idiosyncratic risks), the “differentiation risk” facing these programs has become enormous. And the principal way to discharge differentiation risk is through greater capital intensity and scale – more studies, more indications, more combinations, more head-to-head comparisons – to create broader and better product labels over time. This makes it is especially hard for small venture-backed companies to compete on these targets. Bigger Pharma companies that can aggregate critical mass will clearly have a big advantage in everything from patient access at key clinical centers to “locking up” the key opinion leaders and to share-of-voice with big payors post-approval. Even GSK decided it wasn’t worth competing if you can’t be one of the biggest players in the field.

It will be interesting to watch how the competitive battlefields of erbB, checkpoints, and to a lesser extent CD19 CAR-Ts, play out during the mayhem of #ASCO15 and, more importantly, over the coming few years. When the dust settles, there will be winners and losers that emerge from the ranks of biopharma and their investors – but the real winners from all this competition will ultimately be the cancer patients that get access to better therapies.

Also on Forbes:

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]]>http://www.forbes.com/sites/brucebooth/2015/05/29/asco-2015-abstract-thoughts-on-cancer-and-competition/feed/1BioPharma M&A: Capital Efficiency Drives Returnshttp://www.forbes.com/sites/brucebooth/2015/05/15/biopharma-ma-capital-efficiency-drives-returns/
http://www.forbes.com/sites/brucebooth/2015/05/15/biopharma-ma-capital-efficiency-drives-returns/#commentsFri, 15 May 2015 13:09:00 +0000http://blogs.forbes.com/brucebooth/?p=1080Amidst lofty public markets and robust fund flows, it’s easy to forget the importance of equity capital efficiency in building new biotech companies. But like gravity, it’s a fundamental principle and rests at the heart of generating quality returns in any market. By deploying early, expensive equity dollars carefully and thoughtfully, a startup can preserve its upside in a wide range of market outcomes.

Capitalize a startup too much but fail to achieve escape velocity (or miss the market window), and the inevitable hiccups of drug R&D will severely punish returns. The flip side is also true: starve a company, fail to achieve key milestones, and a challenging fate is sealed. The optimal equity capital efficiency is a goldilocks challenge and has to fit the business opportunity in front of it – one of finely balancing the cost of capital with the burn rate and subsequent value creation within companies (here). The impact of capital efficiency on returns has been discussed many times here in the past (here, here).

A recent Silicon Valley Bank report from Jon Norris and Kristina Peralta caught my attention as it highlights the compelling impact of being smart with your equity dollars if you want to preserve the potential for attractive returns in an M&A setting.

Their report covers the broader funding and exit environment in biotech, and is well worth reviewing. The summary first line captures it all: “The overall boom in healthcare propelled fundraising, investing and exits in 2014 to the highest level in several years, eclipsing our bullish outlook from a year ago.”

But the hidden gem in the data they present was their finding around big exit M&A values, estimated returns, and the impact of equity capital efficiency.

Norris & Peralta looked at 85 M&A exits in BioPharma that were larger than $75M upfront (so called “Big Exits” in their analysis). This includes deals like Alios’ acquisition by J&J, Seragon’s by Genentech, Labrys’ by Teva, CoStim’s by Novartis, and many other exceptional deals. As noted before, the M&A environment in recent years has been very strong (here).

The authors estimated “all-in” returns to investors by taking 85% of the upfront payment and 25% of the future milestones; these are reasonable if not conservative assumptions given the experience with milestone payments recently (here). They created return quartiles in this dataset and looked at the median amount of capital raised in each group.

The findings, re-plotted below as both quartile analysis and a distribution, are striking:

Top quartile return multiples are very attractive – above 8.1x. The companies in this dataset are obviously “winners” in that they attracted >$75M upfront, so its to be expected that this “success biased” quartile distribution would be skewed upward from broader deal datasets. These returns represent top 3-5% outcomes in the VC business.

A few other statistics called out by the authors are worth highlighting:

Within the top quartile, 19/22 deals raised less than $50M in equity capital, and zero raised more than $100M.

Ten deals (in the top quartile) have had M&A return multiples more than 10x of invested capital, and three above 20x.

In the bottom return quartile, 19/21 deals raised more than $50M, and 12 more than $100M.

Since 2009, only two M&A deals with more than $70 million in equity invested returned multiples greater than 4.5x.

A couple caveats are worth calling out in the data. The “big exit value” calculations could be much higher if milestones are paid out, and this could skew the analysis; unclear from the data if there’s more “at-risk” in the lower quartiles than the upper quartiles. Further, these are “all-in” returns, as the authors call it – which means they are an estimate of the weighted average investor returns. Because of this, the actual returns to early or later round investors could greatly differ from these depending on the pricing of the rounds. It’s a good approximation, historically, for estimating returns for investors.

These observations are entirely consistent with prior analysis. In fact, the distribution curve looks remarkably similar to an analysis published in Nature Biotechnology in 2007 called “When Less Is More” on the subject of capital efficiency (see Figure 3a here).

In today’s IPO-centric market, where the cost of capital has been dramatically reduced versus the 2003-2012 period, the opportunity to scale companies more aggressively and earlier in their lifecycle has opened up new options for startups. Having a credible alternative to Pharma M&A via the IPO route has certainly enhanced returns for investors and management teams across the board, and creates a path for building then next Genentech, Vertex, Regeneron, and the like.

Companies like Agios have exhibited remarkable equity capital efficiency in how they have taken advantage of the public market opportunity to scale: the Series A, which brought in a tranched $33M raise, was priced around $3/share, and its trading at 35x that value today. A big part of how Agios and other companies have done this is via creative business development; their landmark deal with Celgene allowed them to scale with non-dilutive funding during a critical time for the company, which opened up multiple options (and new disease areas) to the startup.

If well structured, less dilutive funding mechanisms via creative collaborations can catalyze significant value creation and optionality for young companies. As the SVB authors note:

Thus, companies should look to leverage non-dilutive funding when possible. Many companies started since 2009 have diverse asset pipelines, and partnerships with big biopharma can help by providing non-dilutive funding and validation of the technology. In addition, we have seen an upswing in patient advocacy groups that are providing non-dilutive grants to help defray clinical costs in specific trials. This also provides clinical development opportunities for companies without adding to equity capital.

Its not uncommon in today’s market to see young startups aggressively capitalizing themselves and scaling quickly – the allure of going public early and at lofty valuations has considerable appeal, and can generate great returns if well timed and the markets remain accommodative. If public market investors want to jump into an early stage story at lofty valuations, a startup definitely needs to take the interest seriously. This can be a route to achieving escape velocity – the speed with which one can overcome the constraints of gravity. Over the last decade, there are a number of companies that have done this successfully (and Denali, announced yesterday, may very well become one); but there’s a far longer list of companies who haven’t been able to turn their capital intensity into gravity-defying velocity.

The rocket fuel approach can work well in buoyant markets, but it’s not without its risks. There’s a tradeoff that needs to be balanced; significantly over-capitalizing a startup too early can elevate the risk of less disciplined resource allocation, and it also greatly reduces the degrees of freedom for what an attractive exit path might be – and can often take viable M&A off the table. Although there are exceptions, Pharma by and large won’t regularly pay billions for preclinical assets. Preserving exit optionality has real strategic value.

This new SVB analysis drills home the principle that disciplined equity capital efficiency – and creative business development – provides the opportunity for generating great returns in both M&A and IPO exit environments.

]]>http://www.forbes.com/sites/brucebooth/2015/05/15/biopharma-ma-capital-efficiency-drives-returns/feed/1Scorecard Of Biobuck M&A Earnoutshttp://www.forbes.com/sites/brucebooth/2015/04/30/scorecard-of-biobuck-ma-earnouts/
http://www.forbes.com/sites/brucebooth/2015/04/30/scorecard-of-biobuck-ma-earnouts/#commentsThu, 30 Apr 2015 10:46:00 +0000http://blogs.forbes.com/brucebooth/?p=1073Milestone payments are an important risk-sharing component in today’s biopharma deal-making toolbox. As it’s a topic I’ve explored in the past (here, here), it’s an opportune time to revisit the stats for how they have performed recently.

These contingent value transfers (a.k.a. biobucks) help to bridge the gap in deal expectations, and provide a future reward if a deal withstands the battering of project attrition and advances successfully towards and beyond product approval. Of the $8.4B in VC-backed M&A “value” in 2014, $3.3B was in the form of these biobucks; upfront payments have only been~50% of the total value for most of the last few years.

The conclusion of the prior reviews of this data (links above) suggested that roughly 1/3 of all the payments that were “due” ended up getting paid by the acquirer. The latter blogpost shared some of the data assembled by Shareholder Representative Services, or SRS, which is a firm specializing in working for the selling party’s shareholders to follow up post-acquisition to ensure that escrows are paid, diligence is done, and milestones are tracked.

As of mid-2012, SRS had assembled a small but meaningful dataset of life science deals (biopharma and medtech) where 25 earnout payments had “come due” and were part of the analysis. All the deals in that dataset were rather young as many of these deals had only closed in the prior year or so, hence the limited number of actual earnout payments in that analysis.

Fast forward to the present and, as of April 2015, this dataset has gotten significantly larger. They now track more than 400 separate milestones, including 128 events that have come due (so 5x larger than the prior dataset). These milestone events represent $3.4B in value. Of these milestones, 55 events were in biotech and 73 in medtech.

Surprisingly, given how small the initial 2012 sample set was, these new data have largely continued to track with the original observations: over 1/3 of the expected milestones have paid out.

As per the chart below, across all life science M&A earnouts in these SRS data, 38% of the events and 41% of the value have already been paid out; 41% of the events and 35% of the value have been missed, with the remainder delayed with roughly equal shots at hitting/missing. For biotech only, the numbers are similar but slightly less: 34% of the events and 36% of the value have already been met and paid.

Other nuggets in their recent data review:

Almost all the milestones that have been paid to date were associated with “diligence requirements” for the acquirer to use “commercially reasonable efforts” (or more specific language). Those deals with less stringent diligence requirements saw fewer milestone payouts. No surprise here.

Disputes between the buyer/seller regarding the payment of an earnout have occurred in 30% of the deals in the dataset, mostly related to disagreements over lack of progress or changed timelines.

Earnout renegotiation occurred in 16% of deals, including a few where acquirers returned product rights to the sellers.

Considering the significance of milestones to generating outsized returns in life science M&A deals, these data are further reinforcement that a meaningful proportion will be getting paid.

Last week the quarterly Thomson Reuters data on venture capital funding came out via the National Venture Capital Association (NVCA); beyond the top-line data, there are a few interesting takeaways, especially when viewed in the context of historical trends. Here are six data-driven observations and the supporting charts, derived from the 1Q 2015 PricewaterhouseCoopers/NVCA MoneyTree™ Report.

Overall biotech venture funding levels are amongst the strongest in the sector’s history. As the chart below reveals, three of the top funding quarters in a decade occurred in the last year (far right side). To smooth out the quarterly ups and downs, I’ve plotted the 3Q-rolling average to get a better sense of the trends. Interestingly though, while absolute funding levels are up, the number of biotech companies getting venture financing has largely been flat, running at ~120 companies per quarter. Elevated funding levels don’t appear to be driving increases in biotech formation. The combination implies that the average financing size has gone up, now 50% above the 10-year average (just shy of $14M per financing).

Later rounds of financing have driven the uptick in the overall venture funding numbers, up 60% from its 3Q-rolling average. My guesstimate is that nearly all of this run-up in funding is due to “crossover” activity from traditionally buyside investors joining private company rounds, or roughly ~$500M per quarter for the past year. Unfortunately, it’s very difficult to track the specifics to dissect this topic with any accuracy. The other source of the uptick could be new venture funds coming online, but capital is rarely put to work that quickly out of the gate (i.e., 15-20% in the first year of the fund’s life is common), so the near-term quarterly impact from new venture funds is likely to be minimal.

The surge in biotech venture funding has brought an increase in quarterly “volatility” relative to historical trends. The chart below highlights a decade of quarterly volatility, as measured via an eight-quarter rolling standard deviation normalized to 2010. The significant spike in recent quarters reflects two things: (a) lumpy fund flows caused by “mega-rounds”, like the $450M raise at Moderna, that were less common a few years ago; (b) the fickle but significant fund flows from crossover investors in later rounds of financing, as noted above. For instance, in 1Q 2014, after the Gilead HCV pricing issue spooked the public markets, quarterly venture funding fell below its decadal average as crossover investors closed their wallets (see drop in overall and later rounds of financing above). Volatility is to be expected if crossovers remain engaged in this part of the market, so we should anticipate more ups and downs in quarterly venture funding numbers going forward.

First-time venture financings – those backing new biotech startups – continue to be constrained. The number of new startups per quarter has largely been flat for the past five years, hovering between 20-30 new companies, as I’ve discussed in the past (here, here); as expected, the range-bound trend held up in 1Q 2015. The drop in the pace of startup creation between 2008-2010, which was in part a function of the collapsing number of active venture firms (here), has yet to rebound and appears to be structural.

However, the 1Q 2015 data did show a huge increase in first financing funding levels; in fact, it recorded over $400M in fund flows, the biggest ever quarter. I’m not one to focus on quarterly ups and downs given the volatility mentioned above, as this could just be noise in the lumpy data, but this is over a 2x increase above the norm. Unlike the uptick in later rounds of funding, this additional $200M above historic averages could be due to new venture funds coming online.

Further, since the numbers of new startups has been range-bound for years, this implies that the average funding per startup went up dramatically; for first time in two decades of tracking quarterly data, theaverage financing for a first round in biotech was bigger than the average financing for later rounds, topping over $14.0M. Likely just a fluke, but interesting to see.

These data also imply a shorter than expected “venture financing lifecycle” in biotech. Over time, about 25% of any given quarters’ financings are for newly-backed biotech startups (“first financings”); further, the overall number of quarterly biotech financings has been relatively constant at ~120 companies. Since these numbers are fairly constant over long time intervals, this implies that the typically life of a venture-backed biotech (at least with regard to their venture financing needs) must be about ~4 years. These data suggest that within that period of time, most biotechs must seal their fate – either via death (shutting down) or by no longer needing venture funding (e.g., IPO, M&A, or non-dilutive deal-making self-sufficiency). Otherwise, if it took a longer time on average to reach that fate, we’d see an increasing pool of biotech companies getting venture financed over time, which we largely haven’t over the past decade. This 4-year lifetime is far shorter than commonly perception and warrants further analysis.

Are we in a venture funding bubble? These data certainly can’t answer that. We’ve obviously had a few large quarters for fund flows into venture-backed biotech, but in the vein of “we-aren’t-as-bubbly” as other sectors, a comparison of biotech vs all other venture capital fund flows suggests we aren’t out ahead of the pack. Tech venture financing levels have witnessed massive increases in recent quarters (i.e., the 3Q-rolling average is up ~100% in two years), making the ~30% upswing in biotech venture look modest and decidedly unbubblicious.

It will be interesting to watch the quarterly trends throughout 2015: Will the aggregate biotech funding levels continue? Will the 1Q surge in new startup funding revert to the mean, or will we see more first-time financings and greater new venture formation? Will later rounds of financing continue to attract crossover interest? Will funding numbers increase further or stabilize with less volatility as recent VC fundraising comes online

]]>http://www.forbes.com/sites/brucebooth/2015/04/21/data-snapshot-venture-backed-biotech-financing-riding-high/feed/0Biotech IPO Performance: Discerning Market Or Rising Tide?http://www.forbes.com/sites/brucebooth/2015/03/20/biotech-ipo-performance-discerning-market-or-rising-tide/
http://www.forbes.com/sites/brucebooth/2015/03/20/biotech-ipo-performance-discerning-market-or-rising-tide/#commentsFri, 20 Mar 2015 11:00:00 +0000http://blogs.forbes.com/brucebooth/?p=1056As anyone following the biotech sector knows, the market for new public offerings has been incredibly strong over the past couple years. And the larger cap stocks in the sector have also outperformed, propelled by product launches and exciting clinical data (like Biogen’s aducanumab data today). The strength of the biotech sector has led many to raise the concern of a BioBubble in valuations (here), and sound the alarm.

While it’s certainly fair to say we’ve been experiencing an extended bull run in biotech, it’s unclear to me how much is driven by the evolving view that the fundamentals of biotech investing are changing. Specialist investor ranks are deeper and more sophisticated than ever before. More emerging biotech stocks are posting positive and compelling clinical data. The fruits of the genomics revolution of the last two decades are finally ripening, enabling better and more targeted therapies. And more mid-cap growing biotech firms are launching their own products, gathering revenues, and, dare I say, delivering profits, than ever before in the history of the industry. So it’s clearly a maturing sector in many respects.

One measure of a mature sector, though, is pricing discipline. Mature markets are by definition more discerning and efficient markets. They should punish companies that have bad data or lackluster stories, and reward those with great data or more promise – rather than simply move with the sector’s overall ‘beta’ with market sentiment. A rising tide shouldn’t just lift all the boats in a disciplined market.

Interestingly, discerning that difference appears to be what is happening in the post-IPO biotech marketplace today.

Taking a look at the 121 biotech IPOs that occurred from January 2013 through February 2015, as tracked by BMO Capital Markets, the distribution of post-IPO performance is quite broad. As depicted in the pie chart below, nearly a third of the offerings are below their IPO price, and many well below. Another third are up over 25%, and the remaining third are in between. This is a reasonable distribution of outcomes. A more detailed breakdown as a dense column chart with each offering is shown here.

Taking a look at the specific circumstances, the vast majority of the companies that have at least doubled since their offerings (up over 100%) are up because they released great clinical data (rather than just holding onto their first day euphoric “pops”), for example:

Receptos ($RCPT): Since their IPO in spring 2013, they’ve released multiple positive data updates, including the TOUCHSTONE trial last fall (here) with RPC1063, a sphingosine 1-phosphate 1 receptor (S1P1R) small molecule.

Agios ($AGIO): Both AG-221 and AG-120 programs have delivered positive results since the company’s spring 2013 IPO, including last fall with the latter deliving single agent activity in AML (here).

Bluebird bio ($BLUE): In addition to prior data updates, in December 2014 announced striking data in beta-thalassemia (here) with their LentiGlobin BB305 drug product

Tetraphase ($TTPH): Similar to the other examples, the company reported positive newsflow over time but late last year reported positive pivotal Phase 3 IGNITE trial data (here).

Many others with strong post-IPO performances have also had significant and positive clinical progress since their IPOs, including Portola ($PTLA) with ANNEXA (here), Zafgen ($ZFGN) in hypothalamic injury associated obesity (here), Auspex ($ASPX), PTC Therapeutics ($PTCT) in DMD (here), and others. Compelling clinical data has driven the majority of the big stock moves in the IPO cohort.

Of the laggards that have underperformed and are below their IPO prices, most of them have struggled to catalyze investor support because of challenging post-IPO data and newsflow. Again, here are a few examples:

Kalobios ($KBIO): One of the first IPOs on 2013, it has suffered multiple setbacks and is down over 90%: its lead respiratory product failed to demonstrate efficacy in Phase 2 back in Jan 2014 (here), and then a second respiratory product failed in a pseudomonas study (here).

Regado ($RGDO): after a brutal IPO and financing process, the company’s Phase 3 program, REGULATE-PCI, was terminated by its DSMB, sending the stock into a tailspin (here) and eventually a reverse merger with Tobira

Onconova ($ONTX): it’s lead drug, rigosertib, failed in a late stage pancreatic cancer study in fall of 2013, and then again in a MDS trial in early 2014; the stock lost 75% of its value over the first year (here)

Akebia ($AKBA): Originally a high flier, after it published its Phase IIb efficacy data last fall investors questioned the safety issues raised by the study (here); stock is now off 30% or so since its IPO

Certainly there are exceptions to the theme of the “great data, great stock” correlation implied above. Some companies popped because of exuberant sentiments on the day of their offerings and just haven’t retreated, despite a lack of any material new data. But by and large, companies need to have their pipelines perform to be rewarded with appreciating share price above their initial offering in today’s public market.

Another observation worth noting, in line with my prior August 2014 analysis, is the virtuous-vicious cycle at work here: the big are getting bigger, and the small are getting smaller. Companies with “premium” post-money IPO valuations above $200M have posted a median stock performance of 84% since their offerings. Said another way, nearly half of the premium offerings have already doubled in value. In contrast, the median performance of those IPOs with post-money valuations below $200M is a small loss of -1.0%. That’s striking. Interestingly, it’s a variation of a theme that is reminiscent of the Feuerstein-Ratain Rule for oncology startups – that small cap companies have historically not been able to deliver positive data later in the clinic. Are the sub-$200M companies just not posting good data? Its not quite that simple, for sure, though the discrepancy in performance is significant.

To conclude, if there were widespread disregard for negative news, and only euphoric (rather than measured) responses to good news, we’d all be very worried about being at “Peak BioBubble”. Instead, though, the fact that we’re seeing a broad range of performance post-IPO, and a cooling off of the pace of new offerings in 1Q 2015, is suggestive that we’re in a marketplace with some reasonable hallmarks of buyside discipline.

But only time will tell whether the current environment reflects measured data-driven optimism around evolving biotech fundamentals, or just overwhelmingly irrational exuberance. We’d all like to believe the former is possible as the sector matures.

]]>http://www.forbes.com/sites/brucebooth/2015/03/20/biotech-ipo-performance-discerning-market-or-rising-tide/feed/1Biotech CEOs: Observations In Thermodynamics And Kineticshttp://www.forbes.com/sites/brucebooth/2015/03/16/biotech-ceos-observations-in-thermodynamics-and-kinetics/
http://www.forbes.com/sites/brucebooth/2015/03/16/biotech-ceos-observations-in-thermodynamics-and-kinetics/#commentsMon, 16 Mar 2015 10:44:00 +0000http://blogs.forbes.com/brucebooth/?p=1049A great CEO makes all the difference, and a poor one destroys a ton of value.

But recruiting great CEOs is often hard, especially when picking, as is most often the case, from a list of potential first-time CEOs. How do you know who is going to be the right fit and profile for a biotech startup?

It’s fair to say that identifying the hallmarks of a new CEO destined for great things (versus those with less stellar outcomes) is therefore one of the best skillsets an investor can possess. In early stage biotech investing, it’s obviously important for an investor to understand the science and to appreciate the art of drug discovery and translational medicine – but it’s the ability to pick, recruit, and cultivate a great CEO that is worth its weight in gold.

There’s often not a lot of science in the recruiting process, nor in how to describe the ideal candidate for a new role.

To have some fun, increase the scientific element of the dialogue, and take metaphorical descriptors way too far, I’ll put forward the CEO profiles can be described through the lens of thermodynamics and reaction kinetics. Let me explain.

Thermodynamics: Endothermic vs exothermic interpersonal styles.

As many readers know, in science, thermodynamics considers the relationship between different types of energy (like heat) in systems, and how it is transferred through output like work performed across and within systems. Generally speaking, there are two types of thermodynamic processes, endothermic and exothermic ones:

Endothermic: of or relating to processes that absorb or consume energy to complete work in a system, e.g., baking bread, photosynthesis, evaporation

Exothermic: of or relating to processes that release energy like light or heat, e.g., the burning of a candle, formation of snow in the clouds, nuclear fission

These concepts can easily be applied to how a CEO engages with teams and people around them.

Endothermic managers primarily consume energy provided by others around them. They are often low-key thinkers, deep on content and R&D experience – frequently scientist-turned-CEOs. When successful, they typically surround themselves with teams that are able to provide the energetic fuel to achieve the vision. There’s a bias amongst endotherms to go off by themselves, often alone with the door shut, to tackle a big intellectual problem before reverting to the group. Solving conflicts in the boardroom with endothermic managers isn’t often comfortable, so a great burden of conflict resolution may fall to the boards themselves. These leaders also don’t tend to be “high maintenance” managers with their teams and Boards; since they don’t give off heat into the system, they typically don’t cause of stress-inducing chaos with “six impossible ideas before breakfast”.

Exothermic managers typically add energy to a room and a leadership team. They are seemingly full of boundless energy, throwing off the joules required to inspire, motivate, and sustain the people around them as they lead their teams on efforts of broad ambition and scope. They are great up on the stage, charismatic in their in support and articulation of the company’s vision. They are adamantly “open door” types, preferring to engage others than to necessarily construct a novel solution all by themselves. They often prefer tackling tough concepts in the boardroom through animated and at times heated discussions. Their bias to add energy can often inefficiently fuel organizational entropy; lots of heat around challenging topics can create waves of thermic disruption in an organization.

You can often feel the difference here in the first meeting with these two types of CEOs; did the initial discussion consume or throw off energy?

As an investor trying to identify talented leaders, while the exothermic executive quickly lights up the room, it often requires several meetings to begin to appreciate the deep competence and attraction of endothermic executives. Either profile can work in leadership, but they are very different – and putting them in an organizational context that supports and “fits” with them is critical. For instance, pairing a endothermic scientist-CEO with a more exothermic CBO is a frequently used configuration.

In some ways, these two characterizations are geeky variations and build upon the overused MBTI personality type dichotomy between E’s and I’s (extraversion and introversion).

Kinetics: Stoichiometric or catalytic organizational impacts.

The second key axis for how a CEO or leader drives value in an organization picks a descriptive metaphor from reaction kinetics, and the difference between stoichiometric and catalytic processes:

Stoichiometric process: one where the inputs are all consumed at a fixed, proportional basis, and the rate of the reaction is largely constant; additive or linear processes

Catalytic processes: ones where inputs can be consumed in greater proportions as the velocity of the reaction is increased (in catalysis); synergistic or non-linear processes

As before, these two can be aptly applied to the type of organizational impact a leader can have.

Stoichiometric CEOs can be great stewards of the business, superb at executing the plan, meticulous on the details and getting the job done. As Phil Needleman often says, the prize often belongs to finishers. This type of leader takes the inputs and fully converts them into the outputs in an expected, positive way. They are, when successful, excellent executors of the strategy, and getting a drug program or discovery platform from A to B. Most of the time, though, these CEOs are additive and not synergistic to the trajectory of an organization.

Catalytic CEOs, like an enzyme in a reaction, can have outsized impact on the velocity and performance of an organization. They often achieve non-linear changes in an organization, looking around new corners, creating new strategies, deriving new paradigms for how to envision the company and the field at large. They are by definition more strategically inclined than stoichiometric CEOs. Often not great at execution (perhaps distracted by too much enzymatic substrate around them!), they can lose focus at the finish, so are best surrounded by detailed-oriented ‘completers’. Catalytic CEOs can change the vector of a business profoundly.

As with endothermic and exothermic types, stoichiometric and catalytic CEOs can both be successful – but they typically are best fit into different types of companies, are excited by different types of challenges, and require different types of teams around them.

The Sato Matrix

Most CEOs fit into a matrix of these two dimensions. It may be a bit cerebral, but I think it’s a very appropriate pair of axes to define the characteristics of a CEO. Vicki Sato is a friend, mentor, and advisor of mine (and former President and Head of R&D at Vertex), and is always full of pithy ways of framing up issues. She deserves much credit for this matrix, as it came out during a well-caffeinated morning discussion at Henrietta’s a few weeks ago. So I’ve decided to call it the Sato Matrix of Biotech Leadership:

The descriptors in each of the quadrants captures the essence of the CEO profile.

It’s fair to say that the bottom left – stoichiometric endotherms –is probably not a frequently successful CEO profile in biotech, though they can and often are good individual contributors inside of an organization. The other composite profiles have many examples of successful CEOs, though I’ll refrain from applying names to labels to protect the innocent – but most readers can probably think of folks in the biotech world across these profiles.

Picking the right CEO profile for the right business context is critical. Big science drug discovery platforms, opening up new frontiers of biology, are clearly best suited with more catalytic leadership. Asset-centric single product plays frequently do well with a stoichiometric exotherm in charge – someone who can operate a lean virtual biotech and its external R&D partners to deliver on the product strategy. Getting the leadership of a biotech “right” is as much about the CEO profile as it is about getting the appropriate team around them, and the underlying business model.

So next time you are thinking about the CEO role in a company, remember it’s all about thermodynamics and reaction kinetics.